CEBP http://www.cancermicroenvironment.tau.ac.il/welcome2009.html Advances in Breast Cancer Research
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Cancer Epidemiology Biomarkers & Prevention 17, 258, January 1, 2008. doi: 10.1158/1055-9965.EPI-07-2749
© 2008 American Association for Cancer Research
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Null Results in Brief

The Role of Established Breast Cancer Susceptibility Loci in Mammographic Density in Young Women

Eunjung Lee1, Christopher A. Haiman1, Huiyan Ma2, David Van Den Berg1, Leslie Bernstein1,3 and Giske Ursin1,4

1 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, USC/Norris Comprehensive Cancer Center, Los Angeles, California; 2 Institute for Health Promotion and Disease Prevention Research, Keck School of Medicine, University of Southern California, Alhambra, California; 3 City of Hope Comprehensive Cancer Center and Beckman Research Institute, Duarte, California; and 4 Department of Nutrition, University of Oslo, Oslo, Norway

Requests for reprints: Giske Ursin, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Room 4407, 1441 Eastlake Avenue, Los Angeles, CA 90089. Phone: 323-865-0423; Fax: 323-865-0142. E-mail: gursin{at}usc.edu


   Introduction
Top
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Recently, three genome-wide association studies identified and validated multiple novel loci as contributors to breast cancer susceptibility (1-3). In two of these studies (1, 2), the most significant association was with a common variant (rs2981582) in FGFR2, a gene implicated in mammary carcinogenesis (4-6). However, for all loci, the specific biological pathways that are disrupted and the mechanisms through which these common genetic variations contribute to breast cancer risk remain unclear.

Mammographic density (MD) is an important risk factor for breast cancer (7) and might be predominantly inherited (8), but the gene(s) responsible are, to a large extent, unknown. In the present study, we investigated whether these established breast cancer variants are also associated with MD. Given the known effects of postmenopausal hormone therapy on MD (9, 10), we addressed this question in a study of breast cancer patients under the age of 50.


   Materials and Methods
Top
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
This study has previously been described (11). Female patients diagnosed with histologically confirmed first primary invasive breast cancer were identified through the Los Angeles County Cancer Surveillance Program. Eligible cases were U.S.-born and English speaking, white (including Hispanic) or African-American females, ages 20 to 49 years. Among the 2,882 potentially eligible cases, 1,794 (62%) were interviewed. The study was approved by the Institutional Review Board of the University of Southern California. All participants provided written informed consent.

All subjects were interviewed in-person using a structured questionnaire which covered information on standard breast cancer risk factors. We obtained and digitized mammographic films of the contralateral (noncancerous) breast on 639 of 866 women with unilateral cancer for whom we requested mammograms. Estrogen and progesterone receptor information (ER/PR) was abstracted from pathology reports.

Blood specimens were collected from 588 (92%) women with mammograms. DNA was available on 578 women for the current study. The heterogeneity of genetic effects has been observed for some of these variants between African-Americans and other populations, which presumably reflects differences in linkage disequilibrium between these variants and the underlying causal alleles (1, 3). Thus, we limited our analysis to 516 whites (429 non-Hispanic, 87 Hispanic). We genotyped six single nucleotide polymorphisms (SNP; rs889312, rs2981582, rs3803662, rs3817198, rs13281615, and rs13387042) using TaqMan assays as previously described (1, 3). The genotyping call rate was 97% to 98% for all six SNPs. We included 33 blind duplicate samples which had completely consistent results with the original samples. All SNPs were in Hardy-Weinberg equilibrium in each population.

MD was quantified (by G. Ursin) using the University of Southern California Madena computer-assisted assessment method (12). The breast area was outlined by a research assistant trained by G. Ursin. The Madena software counts the area of absolute density as well as the total breast area. The percent mammographic density was equivalent to the amount of absolute density divided by the total breast area.

Statistical Analyses
We examined the association between the carrier status of these SNPs and the mammographic percentage density using multivariable linear regression. The models were adjusted for age at diagnosis, ethnicity, menopause, hormone use, and body mass index 1 year prior to the diagnosis. We examined allele dosage effects because the previous studies support the codominant effects of these variants on breast cancer risk (1-3). We also examined associations by ER/PR status as the effects of rs3803662 and rs13387042 were shown to be stronger in ER+/PR+ cases (3). All P values reported are two-sided. SAS 9.1 was used for all analyses (SAS Institute).


   Results
Top
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Among whites, minor allele frequencies for each of the SNPs were similar to those in the genome-wide studies, except for rs3803662 (0.36), which was slightly more common than in previous studies (~0.25; refs. 1, 3).

We observed no association between these six SNPs and percent mammographic density (Table 1 ). Among the ER+/PR+ patients, rs3817198 was statistically significantly associated with percent mammographic density (Ptrend per allele = 0.020), with the homozygous carriers having an 11% higher percent density than noncarriers (P = 0.030). However, the trends for ER+/PR+ and ER–/PR– cancers did not differ statistically (P = 0.19). For rs3803662 and rs13387042, the variants more strongly associated with risk of ER+/PR+ breast cancer (3), we observed no significant association with the percent density in ER+/PR+ cases.


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  		Table 1. Percentage of MD associated with genotypes in total subjects and by ER/PR status

 

   Discussion
Top
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this study, we found little evidence that established low-penetrance breast cancer susceptibility variants contribute to interindividual differences in MD.

MD represents the amount of stromal and epithelial tissue in the breast (13). Fibroblast growth factor receptors are involved in cell proliferation, migration, and differentiation, and have been implicated in mammary carcinogenesis (4-6). Therefore, we hypothesized that one possible mechanism by which rs2981582 (or the causal allele it is marking) influences breast cancer risk is through altering MD. However, our data suggest that neither this SNP nor the other susceptibility variants that we examined are strong predictors of MD in young women.

Homozygous carriers of rs3817198 variant alleles had higher MD than noncarriers among ER+/PR+ patients, but the formal test for interaction by ER/PR status was not statistically significant. Rs3817198 is located in intron 10 of a gene encoding lymphocyte-specific protein 1, a filamentous actin–binding protein that plays a role in B-cell signaling and the motility of lymphocytes and neutrophils (14, 15). An alternatively spliced isoform of this protein is expressed in fibroblasts (16), and lymphocyte-specific protein 1 overexpression has been observed in certain drug-resistant breast cancer cell lines (17). Although we cannot exclude the possible effect of rs3817198 on MD, our finding on rs3817198 is likely due to chance and needs to be replicated.

Women with homozygous variants in these new loci may be at a 17% to 63% higher risk of breast cancer than noncarriers (1). If this increased risk were strictly due to MD, this should have translated to 9% to 30% differences in MD between homozygous carriers and noncarriers because a difference of 1% in MD has been associated with a 1.5% to 2% difference in risk (18, 19). We had sufficient (80%) power to find 8% to 10% differences between homozygous carriers and noncarriers; however, no such differences were found.

In summary, we found no evidence that the FGFR2 variant (rs2981582) or the other five breast cancer susceptibility loci that we examined (rs889312, rs3803662, rs3817198, rs13281615, rs13387042) are associated with MD in this study of young women.


   Footnotes
 
Grant support: CA17054 and CA74847 from the National Cancer Institute, NIH, 4PB-0092 from the California Breast Cancer Research Program of the University of California, and in part through NIH contract no. N01-PC-35139. The collection of cancer incidence data used in this publication was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. The ideas and opinions expressed herein are those of the authors, and no endorsement by the State of California, Department of Health Services is intended or should be inferred.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 11/ 2/07; accepted 11/ 2/07.


   References
Top
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Easton DF, Pooley KA, Dunning AM, et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 2007;447:1087–93.[CrossRef][Medline]
  2. Hunter DJ, Kraft P, Jacobs KB, et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet 2007;39:870–4.[CrossRef][Medline]
  3. Stacey SN, Manolescu A, Sulem P, et al. Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet 2007;39:865–9.[CrossRef][Medline]
  4. Grose R, Dickson C. Fibroblast growth factor signaling in tumorigenesis. Cytokine Growth Factor Rev 2005;16:179–86.[CrossRef][Medline]
  5. Moffa AB, Ethier SP. Differential signal transduction of alternatively spliced FGFR2 variants expressed in human mammary epithelial cells. J Cell Physiol 2007;210:720–31.[Medline]
  6. Moffa AB, Tannheimer SL, Ethier SP. Transforming potential of alternatively spliced variants of fibroblast growth factor receptor 2 in human mammary epithelial cells. Mol Cancer Res 2004;2:643–52.[Abstract/Free Full Text]
  7. McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006;15:1159–69.[Abstract/Free Full Text]
  8. Boyd NF, Dite GS, Stone J, et al. Heritability of mammographic density, a risk factor for breast cancer. N Engl J Med 2002;347:886–94.[Abstract/Free Full Text]
  9. Greendale GA, Reboussin BA, Slone S, Wasilauskas C, Pike MC, Ursin G. Postmenopausal hormone therapy and change in mammographic density. J Natl Cancer Inst 2003;95:30–7.[Abstract/Free Full Text]
  10. McTiernan A, Martin CF, Peck JD, et al. Estrogen-plus-progestin use and mammographic density in postmenopausal women: women's health initiative randomized trial. J Natl Cancer Inst 2005;97:1366–76.[Abstract/Free Full Text]
  11. Ma H, Bernstein L, Ross RK, Ursin G. Hormone-related risk factors for breast cancer in women under age 50 years by estrogen and progesterone receptor status: results from a case-control and a case-case comparison. Breast Cancer Res 2006;8:R39.[CrossRef][Medline]
  12. Ursin G, Astrahan MA, Salane M, et al. The detection of changes in mammographic densities. Cancer Epidemiol Biomarkers Prev 1998;7:43–7.[Abstract]
  13. Guo YP, Martin LJ, Hanna W, et al. Growth factors and stromal matrix proteins associated with mammographic densities. Cancer Epidemiol Biomarkers Prev 2001;10:243–8.[Abstract/Free Full Text]
  14. Jongstra-Bilen J, Jongstra J. Leukocyte-specific protein 1 (LSP1): a regulator of leukocyte emigration in inflammation. Immunol Res 2006;35:65–74.[CrossRef][Medline]
  15. Howard T, Li Y, Torres M, Guerrero A, Coates T. The 47-kD protein increased in neutrophil actin dysfunction with 47- and 89-kD protein abnormalities is lymphocyte-specific protein. Blood 1994;83:231–41.[Abstract/Free Full Text]
  16. Gimble JM, Dorheim MA, Youkhana K, et al. Alternatively spliced pp52 mRNA in nonlymphoid stromal cells. J Immunol 1993;150:115–21.[Abstract]
  17. Turton NJ, Judah DJ, Riley J, et al. Gene expression and amplification in breast carcinoma cells with intrinsic and acquired doxorubicin resistance. Oncogene 2001;20:1300–6.[CrossRef][Medline]
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  19. Boyd NF, Lockwood GA, Byng JW, Tritchler DL, Yaffe MJ. Mammographic densities and breast cancer risk. Cancer Epidemiol Biomarkers Prev 1998;7:1133–44.[Abstract/Free Full Text]



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